SynthACticBench: A Capability-Based Synthetic Benchmark for Algorithm Configuration
Valentin Margraf, Anna Lappe, Marcel Wever, Carolin Benjamins, Eyke Hüllermeier, Marius Lindauer
In: Genetic and Evolutionary Computation Conference, 2025
[Preprint] HyperSHAP: Shapley Values and Interactions for Hyperparameter Importance
Marcel Wever, Maximilian Muschalik, Fabian Fumagalli, Marius Lindauer
In: CoRR, 2025
Hyperparameter optimization of two-branch neural networks in multi-target prediction
Dimitrios Iliadis, Marcel Wever, Bernard De Baets, Willem Waegeman
In: Applied Soft Computing, 2024
On the Importance of Initialization in Active Learning
Valentin Margraf, Marcel Wever, Eyke Hüllermeier
In: The Weakly Supervised and Cautious Learning Workshop (WSCL), 2024.
MetaQuRe: Meta-Learning from Model Quality and Resource Consumption
Raphael Fischer, Marcel Wever, Sebastian Buschjäger, Thomas Liebig
In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), 2024.
Position Paper: Why We Must Rethink Empirical Research in Machine Learning
Moritz Herrmann, F Julian D Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
In: Proceedings of International Conference on Machine Learning (ICML), 2024.
[Preprint] ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data
Valentin Margraf, Marcel Wever, Sandra Gilhuber, Gabriel Marques Tavares, Thomas Seidl, Eyke Hüllermeier
In: CoRR, 2024.
Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO
Jasmin Brandt, Marcel Wever, Viktor Bengs, Eyke Hüllermeier
In: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2024.
[Preprint] Information Leakage Detection through Approximate Bayes-optimal Prediction
Pritha Gupta, Marcel Wever, Eyke Hüllermeier
In: CoRR, 2024.
Cooperative Coevolution of Ensembles of Nested Dichotomies for Multi-Class Classification
Marcel Wever, Miran Özdogan, and Eyke Hüllermeier
In: Proceedings of Genetic and Evolutionary Computation Conference (GECCO), 2023.
Meta-learning for Automated Selection of Anomaly Detectors for Semi-supervised Datasets
Marcel Wever, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier
In: Proceedings of Symposium on Intelligent Data Analysis (IDA), 2023.
PyExperimenter: Easily distribute experiments and track results
Tanja Tornede, Alexander Tornede, Lukas Fehring, Lukas Gehring, Helena Graf, Jonas Hanselle, Felix Mohr, and Marcel Wever
In: Journal of Open Source Software (JOSS), 2023.
Annotation Uncertainty in the Context of Grammatical Change
Marie-Luis Merten, Marcel Wever, Michaela Geierhos, Doris Tophinke, and Eyke Hüllermeier
In: International Journal of Corpus Linguistics (IJCL), 2023.
Algorithm Selection on a Meta Level
Alexander Tornede, Lukas Gehring, Tanja Tornede, Marcel Wever, and Eyke Hüllermeier
In: Machine Learning, 2023.
Naive automated machine learning
Felix Mohr and Marcel Wever
In: Machine Learning, 2023.
Towards Green Automated Machine Learning: Status Quo and Future Challenges
Tanja Tornede, Alexander Tornede, Jonas Hanselle, Marcel Wever, Felix Mohr, Eyke Hüllermeier
In: Journal of Artificial Intelligence Research (JAIR), 2023.
Configuration and Evaluation
Jonas Hanselle, Eyke Hüllermeier, Felix Mohr, Axel Ngonga, Mohamed Ahmed Sherif, Alexander Tornede, Marcel Wever
(Book chapter)
A Review of Methods for Automated Algorithm Configuration
Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeir, and Kevin Tierney
In: Journal of Artificial Intelligence Research (JAIR), 2022.
A Comparison of Heuristic, Statistical, and Machine Learning Methods for Heated Tool Butt Welding of Two Different Materials
Karina Gevers, Alexander Tornede, Marcel Wever, Volker Schöppner, and Eyke Hüllermeier
In: Welding in the World, 2022.
[PhD Thesis] Automated Machine Learning for Multi-Label Classification
Marcel Wever
In: Universitätsbibliothek Paderborn
Automated Machine Learning, Bounded Rationality, and Rational Metareasoning
Eyke Hüllermeier, Felix Mohr, Alexander Tornede, and Marcel Wever
In: ECMLPKDD Workshop on Automating Data Science (ADS), 2021.
Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance
Tanja Tornede, Alexander Tornede, Marcel Wever, and Eyke Hüllermeier
In: Proceedings of Genetic and Evolutionary Computation Conference, 2021.
Replacing the Ex-Def Baseline in AutoML by Naive AutoML
Felix Mohr and Marcel Wever
In: ICML Workshop on Automated Machine Learning, 2021.
Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data
Jonas Hanselle, Alexander Tornede, Marcel Wever, and Eyke Hüllermeier
In: Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2021.
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning
Felix Mohr, Marcel Wever, Alexander Tornede, and Eyke Hüllermeier
In: Transactions on Pattern Analysis and Machine Intelligence, 2021.
A Flexible Class of Dependence-Aware Multi-Label Loss Functions
Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencia, Johannes Fürnkranz, and Michael Rapp
In: Machine Learning, 2021.
AutoML for Multi-Label Classification: Overview and Empirical Evaluation
Marcel Wever, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier
In: Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
Towards Meta-Algorithm Selection
Alexander Tornede, Marcel Wever, and Eyke Hüllermeier
In: NeurIPS workshop on Meta-Learning, 2020.
Extreme Algorithm Selection with Dyadic Feature Representation
Alexander Tornede, Marcel Wever, and Eyke Hüllermeier
In: Proceedings of Discovery Science, 2020.
Hybrid Ranking and Regression for Algorithm Selection
Jonas Hanselle, Alexander Tornede, Marcel Wever, and Eyke Hüllermeier
In: Proceedings of German Conference on AI, 2020.
AutoML for Predictive Maintenance: One Tool to RUL them all
Tanja Tornede, Alexander Tornede, Marcel Wever, Felix Mohr, and Eyke Hüllermeier
In: IoTStream @ ECMLPKDD, 2020.
Reliable Part-of-Speech Tagging of Historic Corpora through Set-Valued Prediction
Stefan Heid, Marcel Wever, and Eyke Hüllermeier
In: Journal of Data Mining and Digital Humanities (JDMDH), 2020.
Run2Survive: A Decision-Theoretic Approach to Algorithm Selection based on Survival Analysis
Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, and Eyke Hüllermeier
In: Proceedings of Asian Conference on Machine Learning (ACML), 2020.
Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets
Marcel Wever, Lorijn van Rooijen, and Heiko Hamann
In: Evolutionary Computation, 2020.
LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification
Marcel Wever, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier
In: Proceedings of Symposium on Intelligent Data Analysis (IDA), 2020.
Programmatic Task Network Planning
Felix Mohr, Theodor Lettmann, Eyke Hüllermeier, and Marcel Wever
In: First ICAPS Workshop on Hierarchical Planning, 2018.
Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking
Alexander Tornede, Marcel Wever, Felix Mohr, and Eyke Hüllermeier
In: Workshop on Computational Intelligence, 2019.
Automating Multi-Label Classification Extending ML-Plan
Marcel Wever, Felix Mohr, Alexander Tornede, and Eyke Hüllermeier
In: ICML Workshop on Automated Machine Learning, 2019.
From Automated to On-The-Fly Machine Learning
Felix Mohr, Marcel Wever, Alexander Tornede, and Eyke Hüllermeier
In: Proceedings of INFORMATIK, 2019.
Grammatikwandel digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff
Marie-Luis Merten, Nina Seemann, and Marcel Wever
In: Niederdeutsches Jahrbuch, 2019.
Programmatic Task Network Planning
Felix Mohr, Theodor Lettmann, Eyke Hüllermeier, and Marcel Wever
In: First ICAPS Workshop on Hierarchical Planning, 2018.
[Preprint] Automated Multi-Label Classification based on ML-Plan
Marcel Wever, Felix Mohr, and Eyke Hüllermeier
In: CoRR, 2018.
Reduction Stumps for Multi-Class Classification
Felix Mohr, Marcel Wever, and Eyke Hüllermeier
In: Proceedings of Symposium on Intelligence Data Analysis (IDA), 2018.
[Preprint] Automated Machine Learning Service Composition
Felix Mohr, Marcel Wever, and Eyke Hüllermeier
In: CoRR, 2018.
Ensembles of Evolved Nested Dichotomies for Classification
Marcel Wever, Felix Mohr, and Eyke Hüllermeier
In: Proceedings of Genetic and Evolutionary Computation Conference (GECCO), 2018.
ML-Plan for Unlimited-Length Machine Learning Pipelines
Marcel Wever, Felix Mohr, and Eyke Hüllermeier
In: ICML Workshop on Automated Machine Learning, 2018.
ML-Plan: Automated machine learning via hierarchical planning
Felix Mohr, Marcel Wever, and Eyke Hüllermeier
In: Machine Learning, 2018.
(WIP) Towards the Automated Composition of Machine Learning Services
Felix Mohr, Marcel Wever, Eyke Hüllermeier, and Amin Faez
In: Proceedings of IEEE International Conference on Services Computing (IEEE SCC), 2018.
On-The-Fly Service Construction with Prototypes
Felix Mohr, Marcel Wever, and Eyke Hüllermeier
In: Proceedings of IEEE International Conference on Services Computing (IEEE SCC), 2018.
Automatic Machine Learning: Hierarchical Planning versus Evolutionary Optimization
Marcel Wever, Felix Mohr, and Eyke Hüllermeier
In: 27th Workshop on Computational Intelligence, 2017.
Active Coevolutionary Learning of Requirements Specifications from Examples
Marcel Wever, Lorijn van Rooijen, and Heiko Hamann
In: Proceedings of Genetic and Evolutionary Computation Conference (GECCO), 2017.